Background: Diffusion MRI tractography can support patient-specific neurosurgical planning, but implementation may be limited by workflow complexity, software requirements, and resource constraints. We describe Tractometric^®, a diffusion tractography software engine developed for integration with the Surgimetric^® neuronavigation planning environment. Methods: Tractometric^® was developed through a multidisciplinary, iterative co-design process involving neurosurgeons and neuroimaging specialists. The software uses a modular Model–View–Controller architecture implemented in Python (version 3.11) and supports multiple diffusion reconstruction models, deterministic and probabilistic tracking, patient-specific and atlas-derived regions of interest (ROIs), visualization, and interoperable export. The present study was designed as a technical development and preliminary clinical feasibility report. Technical workflow characteristics were described retrospectively across 30 cases, while preliminary clinical feasibility was explored in 8 patients undergoing tractography-assisted surgical planning. Intraoperative direct cortical and subcortical electrical stimulation was used as a qualitative clinical reference rather than as a formal diagnostic-accuracy test. Results: Tractometric^® implemented a complete workflow from diffusion data loading and preprocessing to tract reconstruction, filtering, visualization, and export to Surgimetric^®. The 30-case technical series illustrated variation in processing time and user interaction according to operator experience, reconstruction model, registration, ROI strategy, and manual cleaning. In 8 preliminary clinical cases, reconstructed motor and language pathways were qualitatively concordant with positive intraoperative stimulation findings. No formal sensitivity, specificity, spatial agreement, or test–retest reproducibility estimates were calculated. Conclusions: Tractometric^® provides an integrated technical workflow for diffusion tractography and neuronavigation planning and was feasible to implement in a preliminary clinical series. The current data support technical feasibility and workflow integration, but do not establish anatomical accuracy, reproducibility, clinical efficacy, or cost-effectiveness. Independent, prospective validation using standardized acquisitions, predefined tractography parameters, quantitative spatial metrics, and systematic intraoperative mapping is warranted.